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- W2916438664 abstract "Identification of useful items that can be picked up from the damaged crops or batch of fruits/vegetables is a challenging task nowadays. Humans may fail to identify them correctly with their naked eyes due to strain. Image processing techniques can help to maximize the amount of the good agro-items easily by comparing the existing goods to templates. This chapter introduces an effective recognition method to spot good agro-items by extracting the local features using Gabor filter for orientation information. Another local information of that fruit/vegetable is extracted by speeded up robust features (SURF) algorithm. The extracted features are matched with their templates which results in the decision of individual feature extraction method. Finally, both local information is fused at decision level individually with AND operation (i.e., both algorithms will give correct decision to identify the good agro-item)." @default.
- W2916438664 created "2019-03-02" @default.
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- W2916438664 date "2019-01-01" @default.
- W2916438664 modified "2023-09-27" @default.
- W2916438664 title "Identification of Good One From the Damaged Crops/Fruits Using Decision-Level Information Matching" @default.
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- W2916438664 doi "https://doi.org/10.4018/978-1-5225-8027-0.ch003" @default.
- W2916438664 hasPublicationYear "2019" @default.
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